Background

This section provides some background material on the topic of dynamic spectrum management. For more detailed background material, interested readers are referred to Leaves et al. (2004), Akyildiz, Lee, Vuran, & Mohanty (2006), Zhao & Sadler (2007), and the references therein. A Venn diagram illustrating the similarity and differences between the algorithms discussed in the background material is shown in Figure 1.

Figure 1.

Venn diagram illustrating the similarity and differences between the algorithms discussed in the background material

Yu, Ginis, & Cioffi (2002) introduced Iterative Water Filling (IWF), one of the first distributed DSM algorithms. In IWF, each user selfishly performs their own power allocation without any regard for their effect on the other users until a point where no user benefits from changing its current power allocation is reached. While IWF gives significant performance improvements over SSM techniques, in many situations, it leads to sub-optimal performance.

Semi-Centralized Algorithms: Algorithms which make use of both a central hub and distributed processing to perform the power allocations using a per-iteration message passing system.

Locally Optimality: Refers to an operating point which is the best within some neighbourhood (i.e., subset of the domain) with respect to some objective (e.g., maximum sum-rate, minimum transmit power).

Nash Equilibrium: A non-cooperative game theoretic solution where no user can gain by changing their current power allocation strategy.

Distributed Algorithms: Algorithms in which users self-optimize fully autonomously without the need of explicit message passing.